Tableau Ambassador Spotlight - Tom Wildes

A couple of weeks ago, I had the pleasure of interviewing Tom W for the Tableau Ambassador Spotlight. Tom is an Australian native living in New York City where he is either weaving in and out of traffic on his bicycle or vizzing about it in Tableau. Tom has been a member of the community for over three years and has helped countless people with calculations and SQL queries to name a couple. Hope you enjoy this interview as much as I did!

Tracy: How long have you been using Tableau?

Tom: I’ve been using it since 2010, which was version 6.

Tracy: Oh wow, you’ve been using it about as long as I have.

Tom: Yeah, well, I didn’t start very serious. My first ventures using Tableau weren’t terribly successful compared to where I’m at today. I didn’t really start to get serious with it until I started to engage in the community a bit more, which was probably around 2013, 2014.

Tracy: And did you start using it for work?

Tom: I started using it because a colleague back in Australia, at a company I worked for where we were using Business Objects, Crystal Reports, and pretty boring, standard BI type stuff. He was on the Tableau train pretty early on, and he was trying to convince us that we should use Tableau as the tool across the enterprise. We actually gave him a nickname as the result of that which stuck to this day which is “Bubbles.” Because he kept showing us Tableau using bubble charts and he was trying to push his agenda on us throughout the organization.

Tracy: That’s hilarious – poor “Bubbles.”

Tom: So that was when I first started using Tableau. In terms of using it in a professional capacity, it wasn’t until I moved to the USA and I picked up some contract / freelance work. A couple of small, short term gigs doing some Tableau reporting, and it was really varied. For example, I did some work for some real estate developers creating maps for potential properties they were looking to purchase. And then, going to the complete other end of the spectrum I completed some slot analysis with some casinos in Las Vegas. It was pretty ad hoc, small projects, but I had to familiarize myself with the tool pretty quickly and realized I didn’t know quite as much as I thought that I did.

Tracy: So you didn’t move over to the States for your job, you moved over for your wife’s job, is that right?

Tom: Well, if you ask her, I moved over for love. But she moved over because she got a job and I came over about nine months later. I didn’t have a job at the time, so I started freelancing when I first arrived, then in 2012, I took a job with a Software as A Service startup company here in the Trade Promotional Management space. I worked with them for two years before joining my current company where I’ve been for a bit over three years.

Tracy: How do you use Tableau at work and/or in your personal life?

Tom: When I joined my current company all our reports were created in Microsoft Excel. So my role was primarily to come in and build a data warehouse, followed by rolling our a new reporting tool. The company had already started a prototype using Pentaho, so I had to work to convince the team to consider Tableau instead. Over the past three years I’ve continued to build out our data warehouse and what we call our ‘data models’ – we implement a new model with every new client project we take on, right now we are somewhere around 25 projects. Early days, I was building data models in SQL, building data visualizations in Tableau, handing them over to the team, they would polish them up, and push them out to our audience or our clients. But nowadays, I’m more like second-tier support in Tableau. I’m not actually implementing things for the team, I push them a data model, they run with it, and implement it in Tableau. When they get stuck with an advanced concept, like a level of detail calculation or some sort of hack, that’s where I come in.

In my personal life I use it for quick analysis without really thinking about – usually a paste from my clipboard into Tableau followed by a quick slice and dice. I follow a couple of “sub-reddits” around cycling. In New York City one of the contentious cycling topics is cars which block bike lanes. There are a couple of websites dedicated to uploading data or photos of where people have found a car blocking the lane. It sounds ridiculous, but as someone who commutes around a lot on their bike, it’s very frustrating (and dangerous!). For the last nine months, the local 311 Authority has published all the data for these reports including the follow up action from the NYPD. Just out of personal curiosity I’ve wanted to see out of the routes that I ride which are the worst effected spots. That’s something where I can take the file off the 311 website, connect in Tableau, and I’ve got it visualized in minutes it versus having to go through individual records and do mental mind mapping.

Tracy: So now do you avoid those routes that have a lot of cars blocking the lanes?

Tom: Yeah, the map is depressing to look at because the lanes are blocked all over the place. But certain precincts are better at reacting to it than others, and that is what was apparent by looking at a view like this. So yeah, I would say that I actually consciously avoid going through those spots.

Tracy: Huh, that’s interesting. I didn’t realize you were such a big cyclist. Have you always been or was it when you moved to New York and you needed alternate forms of transportation?

Tom: I cycle two-fold. We’ve got a bike share program here called, City Bike, with stations all around the city, which is super convenient, so I did that for a while. Then, a friend started a bike company, he’s a manufacturer, so I bought one of his bikes. That’s just my commute to get up and around town, but I cycle for leisure and sport on the weekends. I’ve got a pretty fancy road bike so I ride to Central Park or out to New Jersey. But my typical ride is about 40-50 miles on a Saturday morning.

Tracy: Wow! That’s a long ride. How long does that take?

Tom: It takes 10 miles and 1 hour to get to the George Washington Bridge connecting to NJ. Doing that twice means a 50 mi ride ends up taking at least 4 to 5 hours which is frustrating because you spend a big part of your time just getting to somewhere where it’s finally enjoyable to ride. I normally follow it up with a 3 to 4 hour nap as well!

Tracy: Ha! Well of course, you’ve got to recover! Ok, next question. What type of data interests you? So subject matter or particular data structure or database, whatever.

Tom: Database or technology that I favor would be Microsoft SQL Server as my preferred source. Using SQL enables me to do a lot of things in Tableau which people without SQL cannot. So I like to do as much preparation on the actual database side before I even get into Tableau. That used to be way more relevant than it is today. Fixing data structures to work around limitations within Tableau, I feel like used to be way more relevant than it is today. Other favorite data types? JSON, I use a lot because we use a lot of things like web scraping projects or I do a lot of web application development for my company as well. The standard for transmitting data in those applications is JSON, as I result I end up working with a lot of data in that format.

In terms of subject matter, I find the things I can relate to are the most interesting. My first job out of college was working at Foster’s (“Australian for beer”) back in Melbourne, Australia. That subject matter for a 21 year old coming fresh out of college was amazing. I had friends that were going to work at banks and insurance companies, and that seemed a bit boring. I had a free bar on Thursday and Friday nights, and during the day I got to query databases on the sales of beer, the bestselling products, seasonality across the industry etc. Today, the datasets I find interesting are still the ones I can relate to i.e. the cycling example

Tracy: What was your undergrad?

Tom: It’s called a Bachelor’s of Information Technology. It’s not the most impressive in terms of title, but it was about a 50-50 mix of business related skills (things like accounting and marketing) and then computer science – so databases, Java software development, COBOL (this was in 2004 as well)!

Tracy: How have you learned to use Tableau?

Tom: I started getting my hands dirty. I took on those jobs, not having a really great appreciation for the tool or what was possible, or how to use it. I just saw that our friend “Bubbles” could use it, and I knew how technically capable he was, and I thought that therefore, I should be capable, as well. I quickly realized I was in over my head, but the intuitiveness of the tool made it possible. Not easy, but possible. Essentially everything was self-taught. As soon as I came up across my first roadblock (and you can trace this on my profile), I was on the Tableau Community asking questions. I think @Matt Lutton was one of the first people to reply to me. So the journey I took is kind of the role I support today in the Tableau Community – very much, a trial and error, following intuition, and then asking questions. I don’t think I ever properly ever sat down and consumed a Tableau manual or training video, and I think that is truly a testament to the tool.

Tracy: The manuals and the video can be a little boring, but they’re helpful!

Tom: Well, if you just go through my post history for this week, I’ve probably told about 10 people to go look at the manual and watch the training videos. But, you know, different mechanisms work for different people. For anyone who joins my team, I have a list of the videos off the training website that is my mandatory introduction into Tableau they have to run through. Some people will work better taking a data set and pulling it in, and it will be naturally intuitive to them. But, everybody has different skill levels, especially in a tool like Tableau that can reach the most technical DBA to the marketing intern who has no idea even about Excel. We all learn a bit differently.

Tracy: What is your favorite Tableau project that you’ve worked on?

Tom: We did some stuff on the Google Fiber project where we were commissioned to go out into Kansas City where they were rolling Google Fiber out and conduct a serious of 4,000 door knocks. We were asking people if they were considering Google Fiber, were they not, who they were with, if they were leaving their existing provider, what tier of service were they going to take up, how much were they going to spend etc. Once we put that data into some maps in Tableau, we could map by census track and income levels where things were shifting in the city. The whole hypothesis of Google Fiber was not so much to give people better broadband as the primary objective, but to see what happens to a city if you deliver a minimum level of service to an entire metropolitan area. How did their behaviors shift? Did people start go to the doctor via webcam instead of actually going out? Will they shop more online? So we got to analyze some interesting potential side effects of that rollout. Partly on the side of Google, like big blue sky aspect of things, but also revenue-wise, what that was going to mean to the existing companies that already served that area, and how they would be impacted by a company like Google coming through and providing a new service.

It really only turned out to be a couple of dashboards, but it analyzed our 4,000 door knocks across the entire city of Kansas City.

Tracy: That’s super cool. Some interesting stuff that you must’ve been a part of right as that was starting to take off. What is your favorite feature within Tableau?

Tom: Level of detail calculations. It’s one of the biggest revelations for us. For a very long time I had to build data models in the database which pre-aggregated things to levels that made sense as that was always difficult to do within the front end of Tableau based on our transactional and raw data. I find myself doing a lot more now with level of detail calcs based off of the lowest level of data within the tool versus having to pre-aggregate things in an external tool and bring them in. I don’t think it’s the sexiest feature of Tableau by any means, but it is probably the one that I was most excited about when it got rolled out.

Tracy: Well, and obviously it had a big impact on your day to day job and workflow.

Tom: Yeah, and it’s made it possible for my team to be more self-sufficient in terms of writing calculations.

Tracy: What about on the flip side, what would be your biggest feature request?

Tom: I’m tapping the microphone here, “Hello, Tableau!” I just want when you comment inside a calculation for the text to turn green. I have an idea – everyone, go vote for my idea! (https://community.tableau.com/ideas/3224).

I don’t think this feature is highly utilized, but when I do use it, I find that the comments are hard to read, they’re kind of a chocolate/mocha color, and it blends in with the actual calculation you’re writing. So I told the devs at the last two conferences about it, and it changed in 10.1 I think but it got harder to read! So that’s my burning feature. The day that comes out, I’ll be up there clapping and cheering at Tableau Conference when Christian announces that they’re changing the comment color.

Tracy: That’s a new one! I haven’t ever heard anyone request that as their biggest feature request, but you know, I can understand your frustration.

Tom: Well, look, you know, it’s tongue in cheek, but I think that’s a representation of how far the tool has come in recent years. I’m certainly excited about the prospect by some of the stuff that was presented at TC16 around data model governance. Like the published data sources where you’re able to have comments around what different fields mean in that data source. Talking about limitations or caveats around that – I probably see about a post a week, where I wish we could be talking about that, and I wish that feature already existed because it would totally solve this problem. So I’m building road maps in my mind around that function which hasn’t yet been released. So I’ll bump down the priority of comments and everybody can stand down of changing that color, if they’re able to prioritize that data governance aspect because I think that would really help us a lot, and change the maturity of Tableau, itself. It started off with people using Excel and Tableau on their desktops. It’s come a long way to be where it is today, but if things aren’t managed properly, data governance can become a massive problem.

Tracy: How did you discover the Tableau Community?

Tom: I think it was a natural intuition based on my background. I had contributed to forums in other technology products. From my early years, I would go on forums for other various interests, things like music and bands. But, when I had a problem or question, my first reaction was that I need to find a forum. There have to be other similar people out there like me who have similar questions and want to learn more about the tool. So, I set out to find that. It was obviously pretty straight forward. A quick Google search, and then once I came across the community I submitted couple of questions. As my questions were answered, I found myself wanting to try and answer other people’s questions. Seeing that I was unable to answer those, made me want to learn how I could answer that person’s question. I went there to have certain problems solved, but then ended up learning so much more about the tool by trying to solve other people’s problems.

Tracy: It’s one of the best ways to learn. It’s like answering support questions.

Tom: And that’s why I’m still interested and engaged today. I don’t just try to pick the things that I consider myself as a subject matter expert at. I try to challenge myself to pick up something that I don’t know how to do. Invest a little time, and actually learn the areas that you’re weakest in, and pick up some new skills.

Tracy: What is your favorite part about the Tableau Community?

Tom: Being surrounded by like-minded people who are dedicated to the cause, not that there’s a “cause”, but being alongside other people who are really competent in the tool and want to help others. There’s a sense of camaraderie there that is pretty special. There are people from the internet that I visualize their face on a daily basis as they’re replying to other people’s threads, because I’ve caught up with them and had a beer at the Tableau Conference and what not.

Tracy: What advice do you have for people new to Tableau and/or the Tableau Community?

Tom: To new users of Tableau I would encourage them to follow a path that suits their learning style best – if you like to get your hands dirty and learn from your mistakes, go ahead and jump in. If you work better with hands on guidance, follow the many great video tutorials or buy a book – some of the great contributors to this community have written books which I highly recommend!

In the community, my advice would be, help us help you. I often think about this from the lens of if I have a problem with my car, I wouldn’t just call my mechanic and say, “Hey, my car is making this weird noise. It sort of sounds like: clunk clunk clunk. And you’ve heard all the noises a car has made before, so you should just be able to tell me how to fix it without actually seeing my car right?” Give everybody the necessarily level of information that we need to help you, and you’ll get the answer very quickly.

And then, I would obviously, encourage people to continue to contribute in the same way that a lot of us have. Try to answer some other people’s questions when you come and ask yours. Pay it forward. Not because you should pay it forward but because you’ll get so much back in terms of what you learn as a part of that process.